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Yu-Chang Wu

2 accepted papers

2025

Pareto Set Learning for Multi-Objective Reinforcement Learning

AAAI 2025technical

Multi-objective decision-making problems have emerged in numerous real-world scenarios, such as video games, navigation and robotics. Considering the clear advantages of Reinforcement Learning (RL) in optimizing decision-making processes, researchers have delved into the development of Multi-Objecti…

Cited by 1SourcePDFScholar
2024

Confidence-aware Contrastive Learning for Selective Classification

ICML 2024poster

Selective classification enables models to make predictions only when they are sufficiently confident, aiming to enhance safety and reliability, which is important in high-stakes scenarios. Previous methods mainly use deep neural networks and focus on modifying the architecture of classification lay…